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A research group has developed a new learning method for artificial intelligence that combines classification performance for data with multiple labels with the ability to learn continually from data. Numerical experiments on real-world multi-label data indicate that the new method outperforms conventional approaches. The simplicity of this algorithm makes it easy to integrate it with other algorithms to devise new ones.